市场形态周报（20250728-20250801）：本周指数普遍调整-20250803

Quantitative Models and Construction Methods 1. Model Name: Heston Model - Model Construction Idea: The Heston model is used to calculate the implied volatility of near-month at-the-money options, serving as a market fear index. Implied volatility reflects market participants' expectations of future volatility [8] - Model Construction Process: The Heston model is a stochastic volatility model where the variance of the asset price follows a mean-reverting square-root process. The model is defined by the following equations: $ dS_t = \mu S_t dt + \sqrt{v_t} S_t dW_t^1 $ $ dv_t = \kappa (\theta - v_t) dt + \sigma \sqrt{v_t} dW_t^2 $ Here: - $S_t$: Asset price - $v_t$: Variance process - $\mu$: Drift rate of the asset price - $\kappa$: Rate of mean reversion of variance - $\theta$: Long-term variance - $\sigma$: Volatility of variance - $W_t^1, W_t^2$: Two Wiener processes with correlation $\rho$ [8] - Model Evaluation: The Heston model is widely recognized for its ability to capture the stochastic nature of volatility, making it suitable for modeling market fear indices [8] --- Quantitative Factors and Construction Methods 1. Factor Name: Multi-Long-Short Ratio Scissor Difference - Factor Construction Idea: This factor is based on the difference between the number of long and short signals within industry index constituent stocks. It is used to construct industry timing strategies [15] - Factor Construction Process: - Define the number of long and short signals for each industry index constituent stock on a given day - If no long signals are present, set the long signal count to 0; similarly, if no short signals are present, set the short signal count to 0 - Calculate the scissor difference as the difference between the long and short signal counts - Normalize the scissor difference to obtain the scissor difference ratio [15] - Factor Evaluation: The backtesting results show that the timing model based on this factor outperforms the respective industry indices in all cases, demonstrating excellent historical performance [15] --- Backtesting Results of Models 1. Heston Model - Implied Volatility Results: - SSE 50: 13.63% (down 2.78% WoW) - SSE 500: 15.75% (down 3.31% WoW) - CSI 1000: 17.15% (down 3.26% WoW) - CSI 300: 13.96% (down 2.31% WoW) [10] --- Backtesting Results of Factors 1. Multi-Long-Short Ratio Scissor Difference - Performance Metrics: - Timing models based on this factor outperformed their respective industry indices in all cases, achieving a 100% success rate in backtesting [15]